What analytics are available for monitoring Agentforce agent performance?

Agentforce provides several layers of analytics and monitoring:

1. Conversation Logs: Every agent conversation is logged, including the full message transcript, topics classified, actions invoked, action parameters, action outputs, and final responses. Accessible in Setup under Agentforce Agent Analytics. Logs are essential for debugging and quality review.
2. Topic Classification Accuracy: Metrics showing how often each topic was classified, including instances where no topic matched (fallback rate). High fallback rates indicate topic descriptions need refinement or new topics are needed.
3. Action Success Rate: For each action, the percentage of invocations that completed successfully vs failed. Low success rates indicate Flow or Apex errors that need investigation.
4. Resolution Rate: The percentage of conversations where the agent fully resolved the user's request without escalating to a human. This is the primary operational KPI for autonomous agents.
5. Escalation Rate and Reasons: Tracks how often and why the agent escalates — by topic, by action failure, or by user request.
6. Einstein Trust Layer Audit Trail: Provides a compliance-focused log of every LLM call, data masking operation, and toxicity detection event for security and regulatory reporting.